Dietary ModificationNCT03104686
Pasta and Bread Prepared With Durum Wheat Semolina: Effect on Post-prandial Glucose and Insulin Metabolism
A study testing Short pasta (dry), Long pasta (dry) and Bread in people with Dietary Modification, run by University of Parma at 1 site in Italy.
Trial summary
Carbohydrate-based products can influence the post-prandial glycemic response differently based on their ability to be digested, absorbed and to affect rises in plasma glucose. Pasta is one of the major carbohydrate-rich foods consumed in Italy. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Dietary Modification
- What is being tested?
- Short pasta (dry), Long pasta (dry) and Bread
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30 participants
- Where
- 1 siteItaly
- Study dates
- 10 Apr 2017to 15 Jun 2018
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- healthy male and female
Who cannot join
- BMI>30kg/m2
- celiac disease
- metabolic disorders (diabetes, hypertension, dislipidemia, glucidic intolerance)
- chronic drug therapies for any pathologies (including psychiatric diseases)
- intense physical activity
- dietary supplements affecting the metabolism
- anemia
Trial locations and contacts
1 site in 1 country.
About this study
Carbohydrate-based products can influence the post-prandial glycemic response differently based on their ability to be digested, absorbed and to affect rises in plasma glucose. Pasta is one of the major carbohydrate-rich foods consumed in Italy. Studies from the literature describe a lower glycemic response after the consumption of pasta compared with other wheat-based products, such as bread. Among the factors affecting post-prandial glycemia after consumption of carbohydrate-based products, the technological process represents a central one. In fact, the different technological processes alter the food matrix which can affect the post-prandial metabolism of glucose and insulin differently. Thus, the present study aims at investigating the effect induced by the principal steps of the process of pasta production on the reduction of post-prandial glycemic and insulinemic responses.
Read the detailed description
The different glycemic responses after the consumption of carbohydrate-based products are associated with different rates of digestion and absorption of the carbohydrates in the human body. Therefore, food products rich in carbohydrates can be classified based on their ability to be digested, absorbed and to affect post-prandial glycemia. Epidemiological studies suggest that following a diet including carbohydrate-based foods inducing a low and slow glycemic response is associated with reduced risk to develop some non-communicable diseases (such as type 2 diabetes and cardiovascular disease), to control inflammatory status, which is the trigger of several pathologies, and to reduce fasting insulin. Depending on the food composition, a low glycemic response is not always associated with a low plasma insulin concentration. For instance, high protein or lipid concentrations in the food matrix have been demonstrated to induce low post-prandial glycemic responses, but not a reduction in insulin secretion. Avoiding a high insulin post-prandial response after consumption of foods represents a preventive factor against the risk of overweight and hyperlipidemia, type 2 diabetes, and cancer. Therefore, the evaluation of both glycemic and insulinemic post-prandial response curves is necessary in order to demonstrate the true beneficial effect of the consumption of low glycemic index foods. Among several factors which can influence the post-prandial glycemic and insulinemic responses (such as macronutrient composition and the cooking process), the technological aspects through which the foods are produced represent an important one. Several studies reported a low glycemic response after the consumption of pasta compared with bread, and this is due to the technological structures characterizing the two matrices. Pasta is one of the major sources of carbohydrates consumed in Italy. Therefore, the aim of the present study is to investigate the effect of pasta and bread on the plasma response of glucose and insulin, as well as c-peptide in order to clearly discriminate the different biological effect induced by the technological process in the production of pasta, compared to foods beginning with the same ingredients. Moreover, the study aims to create a solid basis for future studies for evaluating the effect of pasta consumption, as the main source of carbohydrates, in a context of a balanced diet, for maintaining health.
- Conditions
- Dietary Modification
- Being tested
- Short pasta (dry), Long pasta (dry), Bread, Glucose
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Short pasta (dry)Other
Also called Penne
50g available carbohydrate of penne pasta
Long pasta (dry)Other
Also called Spaghetti
50g available carbohydrate of spaghetti pasta
BreadOther
50g available carbohydrate of bread
GlucoseOther
50g available carbohydrate of glucose monohydrate
| Study group | Role | What they receive |
|---|---|---|
| Bread | Active comparator | Bread (50g available carbohydrate, 109 g) eaten with 500 mL of water Receives: Other: Bread |
| Short pasta (dry) | Experimental | Cooked penne (142 g; 71 g uncooked) eaten with 500 mL of water Receives: Other: Short pasta (dry) |
| Long pasta (dry) | Experimental | Cooked spaghetti (142 g; 71 g uncooked) eaten with 500 mL of water Receives: Other: Long pasta (dry) |
| Glucose | Active comparator | Glucose monohydrate (55 g) dissolved with 500 mL of water Receives: Other: Glucose |
What is being measured
The primary outcome is the main question the study is designed to answer.
incremental area under the curve for blood glucose
postprandial response for blood glucose (IAUC)
Measured: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
incremental area under the curve for plasma insulin
postprandial response for plasma insulin (IAUC)
Measured: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary outcomes (1)
post-prandial c-peptide plasma concentration
postprandial response for plasma c-peptide (IAUC)
Measured: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Apr 2017
- Study start10 Apr 2017
- Primary completion15 Jun 2018
- Study completion15 Jun 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (17)Papers the sponsor has linked to this study.
- Other trials for Dietary ModificationStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 30 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Parma
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Francesca Scazzina Ph.D., University of Parma
- Investigators
- Francesca Scazzina, PhD, Principal investigator, Department of Food Science, University of ParmaFurio Brighenti, PhD, Study director, Department of Food Science, University of Parma
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03104686
- Sponsor's protocol ID
- Pane2
- Status last verified
- Sep 2018
- First submitted
- 28 Feb 2017
- Last updated
- 12 Sep 2018
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Blaak EE, Antoine JM, Benton D, Bjorck I, Bozzetto L, Brouns F, Diamant M, Dye L, Hulshof T, Holst JJ, Lamport DJ, Laville M, Lawton CL, Meheust A, Nilson A, Normand S, Rivellese AA, Theis S, Torekov SS, Vinoy S. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev. 2012 Oct;13(10):923-84. doi: 10.1111/j.1467-789X.2012.01011.x. Epub 2012 Jul 11.
PubMed 22780564Collier GR, Greenberg GR, Wolever TM, Jenkins DJ. The acute effect of fat on insulin secretion. J Clin Endocrinol Metab. 1988 Feb;66(2):323-6. doi: 10.1210/jcem-66-2-323.
PubMed 3276722Dong JY, Zhang L, Zhang YH, Qin LQ. Dietary glycaemic index and glycaemic load in relation to the risk of type 2 diabetes: a meta-analysis of prospective cohort studies. Br J Nutr. 2011 Dec;106(11):1649-54. doi: 10.1017/S000711451100540X. Epub 2011 Sep 29.
PubMed 22017823Gannon MC, Nuttall FQ, Neil BJ, Westphal SA. The insulin and glucose responses to meals of glucose plus various proteins in type II diabetic subjects. Metabolism. 1988 Nov;37(11):1081-8. doi: 10.1016/0026-0495(88)90072-8.
PubMed 3054432Jenkins DJ, Wolever TM, Jenkins AL. Starchy foods and glycemic index. Diabetes Care. 1988 Feb;11(2):149-59. doi: 10.2337/diacare.11.2.149.
PubMed 3383733Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling AC, Newman HC, Jenkins AL, Goff DV. Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr. 1981 Mar;34(3):362-6. doi: 10.1093/ajcn/34.3.362.
PubMed 6259925Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Am J Clin Nutr. 2013 Mar;97(3):584-96. doi: 10.3945/ajcn.112.041467. Epub 2013 Jan 30.
PubMed 23364021Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA. 2002 May 8;287(18):2414-23. doi: 10.1001/jama.287.18.2414.
PubMed 11988062Ma XY, Liu JP, Song ZY. Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies. Atherosclerosis. 2012 Aug;223(2):491-6. doi: 10.1016/j.atherosclerosis.2012.05.028. Epub 2012 Jun 6.
PubMed 22727193Onitilo AA, Stankowski RV, Berg RL, Engel JM, Glurich I, Williams GM, Doi SA. Type 2 diabetes mellitus, glycemic control, and cancer risk. Eur J Cancer Prev. 2014 Mar;23(2):134-40. doi: 10.1097/CEJ.0b013e3283656394.
PubMed 23962874Ostlund RE Jr, Staten M, Kohrt WM, Schultz J, Malley M. The ratio of waist-to-hip circumference, plasma insulin level, and glucose intolerance as independent predictors of the HDL2 cholesterol level in older adults. N Engl J Med. 1990 Jan 25;322(4):229-34. doi: 10.1056/NEJM199001253220404.
PubMed 2403660Petitot, M., Abecassis, J. & Micard, V. Structuring of pasta components during processing: impact on starch and protein digestibility and allergenicity. Trends Food Sci Tech. 2009;20,521-532
Schwingshackl L, Hoffmann G. Long-term effects of low glycemic index/load vs. high glycemic index/load diets on parameters of obesity and obesity-associated risks: a systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2013 Aug;23(8):699-706. doi: 10.1016/j.numecd.2013.04.008. Epub 2013 Jun 17.
PubMed 23786819Sieri S, Krogh V, Berrino F, Evangelista A, Agnoli C, Brighenti F, Pellegrini N, Palli D, Masala G, Sacerdote C, Veglia F, Tumino R, Frasca G, Grioni S, Pala V, Mattiello A, Chiodini P, Panico S. Dietary glycemic load and index and risk of coronary heart disease in a large italian cohort: the EPICOR study. Arch Intern Med. 2010 Apr 12;170(7):640-7. doi: 10.1001/archinternmed.2010.15.
PubMed 20386010Weyer C, Funahashi T, Tanaka S, Hotta K, Matsuzawa Y, Pratley RE, Tataranni PA. Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia. J Clin Endocrinol Metab. 2001 May;86(5):1930-5. doi: 10.1210/jcem.86.5.7463.
PubMed 11344187
Study at a glance
From the registry record, last updated by the sponsor on 12 Sep 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Pasta and Bread Prepared With Durum Wheat Semolina: Effect on Post-prandial Glucose and Insulin Metabolism
- ClinicalTrials.gov ID
- NCT03104686
- Acronym / sponsor ID
- Pane2
- Conditions
- Dietary Modification
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 30 participants (actual)
- Lead sponsor
- University of ParmaUniversity, hospital or other
- Study start
- 10 Apr 2017 (actual)
- Primary completion
- 15 Jun 2018 (actual)
- Study completion
- 15 Jun 2018 (actual)
- First posted
- 7 Apr 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Carbohydrate-based products can influence the post-prandial glycemic response differently based on their ability to be digested, absorbed and to affect rises in plasma glucose. Pasta is one of the major carbohydrate-rich foods consumed in Italy. Studies from the literature describe a lower glycemic response after the consumption of pasta compared with other wheat-based products, such as bread. Among the factors affecting post-prandial glycemia after consumption of carbohydrate-based products, the technological process represents a central one. In fact, the different technological processes alter the food matrix which can affect the post-prandial metabolism of glucose and insulin differently. Thus, the present study aims at investigating the effect induced by the principal steps of the process of pasta production on the reduction of post-prandial glycemic and insulinemic responses.
Detailed description
The different glycemic responses after the consumption of carbohydrate-based products are associated with different rates of digestion and absorption of the carbohydrates in the human body. Therefore, food products rich in carbohydrates can be classified based on their ability to be digested, absorbed and to affect post-prandial glycemia. Epidemiological studies suggest that following a diet including carbohydrate-based foods inducing a low and slow glycemic response is associated with reduced risk to develop some non-communicable diseases (such as type 2 diabetes and cardiovascular disease), to control inflammatory status, which is the trigger of several pathologies, and to reduce fasting insulin. Depending on the food composition, a low glycemic response is not always associated with a low plasma insulin concentration. For instance, high protein or lipid concentrations in the food matrix have been demonstrated to induce low post-prandial glycemic responses, but not a reduction in insulin secretion. Avoiding a high insulin post-prandial response after consumption of foods represents a preventive factor against the risk of overweight and hyperlipidemia, type 2 diabetes, and cancer. Therefore, the evaluation of both glycemic and insulinemic post-prandial response curves is necessary in order to demonstrate the true beneficial effect of the consumption of low glycemic index foods. Among several factors which can influence the post-prandial glycemic and insulinemic responses (such as macronutrient composition and the cooking process), the technological aspects through which the foods are produced represent an important one. Several studies reported a low glycemic response after the consumption of pasta compared with bread, and this is due to the technological structures characterizing the two matrices. Pasta is one of the major sources of carbohydrates consumed in Italy. Therefore, the aim of the present study is to investigate the effect of pasta and bread on the plasma response of glucose and insulin, as well as c-peptide in order to clearly discriminate the different biological effect induced by the technological process in the production of pasta, compared to foods beginning with the same ingredients. Moreover, the study aims to create a solid basis for future studies for evaluating the effect of pasta consumption, as the main source of carbohydrates, in a context of a balanced diet, for maintaining health.
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| Bread | Active comparator | Other: BreadBread (50g available carbohydrate, 109 g) eaten with 500 mL of water |
| Short pasta (dry) | Experimental | Other: Short pasta (dry)Cooked penne (142 g; 71 g uncooked) eaten with 500 mL of water |
| Long pasta (dry) | Experimental | Other: Long pasta (dry)Cooked spaghetti (142 g; 71 g uncooked) eaten with 500 mL of water |
| Glucose | Active comparator | Other: GlucoseGlucose monohydrate (55 g) dissolved with 500 mL of water |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- healthy male and female
Key exclusion criteria (7 listed)
- BMI>30kg/m2
- celiac disease
- metabolic disorders (diabetes, hypertension, dislipidemia, glucidic intolerance)
- chronic drug therapies for any pathologies (including psychiatric diseases)
- intense physical activity
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Short pasta (dry)Also: Penne50g available carbohydrate of penne pasta | Other | Short pasta (dry) |
| Long pasta (dry)Also: Spaghetti50g available carbohydrate of spaghetti pasta | Other | Long pasta (dry) |
| Bread50g available carbohydrate of bread | Other | Bread |
| Glucose50g available carbohydrate of glucose monohydrate | Other | Glucose |
Primary outcome
incremental area under the curve for blood glucose
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
postprandial response for blood glucose (IAUC)
incremental area under the curve for plasma insulin
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
postprandial response for plasma insulin (IAUC)
1 secondary outcome
post-prandial c-peptide plasma concentration
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Sep 2018.
- Background: PubMed 22780564Blaak EE, Antoine JM, Benton D, Bjorck I, Bozzetto L, Brouns F, Diamant M, Dye L, Hulshof T, Holst JJ, Lamport DJ, Laville M, Lawton CL, Meheust A, Nilson A, Normand S, Rivellese AA, Theis S, Torekov SS, Vinoy S. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev. 2012 Oct;13(10):923-84. doi: 10.1111/j.1467-789X.2012.01011.x. Epub 2012 Jul 11.
- Background: PubMed 3276722Collier GR, Greenberg GR, Wolever TM, Jenkins DJ. The acute effect of fat on insulin secretion. J Clin Endocrinol Metab. 1988 Feb;66(2):323-6. doi: 10.1210/jcem-66-2-323.
- Background: PubMed 22017823Dong JY, Zhang L, Zhang YH, Qin LQ. Dietary glycaemic index and glycaemic load in relation to the risk of type 2 diabetes: a meta-analysis of prospective cohort studies. Br J Nutr. 2011 Dec;106(11):1649-54. doi: 10.1017/S000711451100540X. Epub 2011 Sep 29.
- Background: PubMed 3054432Gannon MC, Nuttall FQ, Neil BJ, Westphal SA. The insulin and glucose responses to meals of glucose plus various proteins in type II diabetic subjects. Metabolism. 1988 Nov;37(11):1081-8. doi: 10.1016/0026-0495(88)90072-8.
- Background: PubMed 3383733Jenkins DJ, Wolever TM, Jenkins AL. Starchy foods and glycemic index. Diabetes Care. 1988 Feb;11(2):149-59. doi: 10.2337/diacare.11.2.149.
- Background: PubMed 6259925Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling AC, Newman HC, Jenkins AL, Goff DV. Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr. 1981 Mar;34(3):362-6. doi: 10.1093/ajcn/34.3.362.
- Background: PubMed 23364021Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Am J Clin Nutr. 2013 Mar;97(3):584-96. doi: 10.3945/ajcn.112.041467. Epub 2013 Jan 30.
- Background: PubMed 11988062Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA. 2002 May 8;287(18):2414-23. doi: 10.1001/jama.287.18.2414.
- Background: PubMed 22727193Ma XY, Liu JP, Song ZY. Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies. Atherosclerosis. 2012 Aug;223(2):491-6. doi: 10.1016/j.atherosclerosis.2012.05.028. Epub 2012 Jun 6.
- Background: PubMed 23962874Onitilo AA, Stankowski RV, Berg RL, Engel JM, Glurich I, Williams GM, Doi SA. Type 2 diabetes mellitus, glycemic control, and cancer risk. Eur J Cancer Prev. 2014 Mar;23(2):134-40. doi: 10.1097/CEJ.0b013e3283656394.
- Background: PubMed 2403660Ostlund RE Jr, Staten M, Kohrt WM, Schultz J, Malley M. The ratio of waist-to-hip circumference, plasma insulin level, and glucose intolerance as independent predictors of the HDL2 cholesterol level in older adults. N Engl J Med. 1990 Jan 25;322(4):229-34. doi: 10.1056/NEJM199001253220404.
- BackgroundPetitot, M., Abecassis, J. & Micard, V. Structuring of pasta components during processing: impact on starch and protein digestibility and allergenicity. Trends Food Sci Tech. 2009;20,521-532
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Francesca Scazzina, PhD principal investigator
Department of Food Science, University of Parma
Furio Brighenti, PhD study director
Department of Food Science, University of Parma
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Short pasta (dry), Long pasta (dry) and Bread in people with Dietary Modification, run by University of Parma at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 12 Sep 2018. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
incremental area under the curve for blood glucose (time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03104686, which also lists 17 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Sep 2018.